Predicting underwater ambient noise with an evolutionary signal processing method

Abstract

In this report we employ recent developments in non-linear physics and time series prediction to study the physical characteristics of measured underwater ambient sounds. Specifically, we examine the predictability of a sample of ocean ambient noise recorded in the Strait of Sicily, Italy. An approach based on genetic algorithms has been employed. Results indicate that, while showing complex time variability, the recorded signals are highly predictable.